Using genetics and social factors to predict opioid use disorder
Official title: Predictive Models for Opioid Use Disorder Using Genomic, Social, and Clinical Factors
Funded at University of California, San Diego · NIH-10930115 · Data updated 2026-11-12
This study is looking to help people at risk for opioid use disorder by using genetic and social information to create tools that can predict who might develop this condition, especially focusing on those from underrepresented groups.
Quick facts
| Grant type | R03 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Diego NIH-funded |
| Lab location | 1 site (La Jolla, United States) |
| Project start | September 15, 2023 |
| Project end | August 31, 2025 |
| Funding year | 2024 |
| Award (this year) | $118,500 |
| NIH project number | 5R03DA059748-02 |
| Project ID | NIH-10930115 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals over 21 years old who may be at risk for opioid use disorder, particularly those with co-existing pain conditions.
✕Less likely to help
Patients who are not at risk for opioid use disorder or those under 21 years old may not receive any benefit from this research.
What this research studies
This research aims to tackle the opioid crisis by developing predictive models for opioid use disorder (OUD) that incorporate genomic, social, and clinical factors. By utilizing the diverse AllOfUs database, the project will analyze genetic markers and other relevant data to identify individuals at risk for OUD. Machine learning techniques will be employed to create models that can classify risk levels, potentially leading to better prevention and treatment strategies. The study focuses on understanding how various factors contribute to OUD, especially in underrepresented populations.
Why it matters
Potential benefit: If successful, this research could lead to more accurate predictions of opioid use disorder, enabling targeted interventions and improved patient outcomes.
How similar studies have gone: Previous research has shown promise in using machine learning and genomic data to predict various health outcomes, suggesting that this approach could be effective for opioid use disorder as well.
Where this research is happening
-
University of California, San Diego
La Jolla, United States Active
Researchers
- Principal investigator: Gabriel, Rodney Allanigue — University of California, San Diego
- Study coordinator: Gabriel, Rodney Allanigue
Related research
Other NIH-funded projects on the same topics.
-
Systems analysis to improve opioid use disorder care after jail release (SAIA-MOUD)
A program to help people with opioid use disorder get better, faster, and safer care after they leave jail.
-
Precise epigenetic drugs for opioid addiction
A tiny, targeted drug approach is being developed to help people with opioid use disorder by rewriting the epigenetic signals in the brain to reduce cravings and relapse risk.
-
Increasing Access to Medications for Opioid Use Disorder for Unhoused Montanans
This project helps unhoused people in Montana get life-saving medicines for opioid use disorder through clinics connected to syringe service programs, a nurse-led MOUD model, and peer support.
-
Optimizing long-acting PrEP and opioid treatment for people in jails and prisons
This project tests a real-world approach to using long-acting PrEP and buprenorphine for HIV prevention and opioid treatment among incarcerated individuals and after release.
-
Scaling up medications for opioid use disorder in residential treatment programs
This grant studies how to help residential treatment programs provide medications for opioid use disorder to reduce overdoses after discharge, focusing on real-world settings and policies.
-
Increasing Capacity at a Native Community Clinic to Improve Opioid Care for urban AI/AN
This grant helps a Native American health clinic build its research capacity to better serve urban American Indian and Alaska Native people dealing with opioid use disorder and related health issues.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.